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Magnus Hedemark 5428b18ddd feat: add autogen — expert skill for conversational multi-agent AI

Greenfield SkillOpt: 3 epochs for Microsoft AutoGen skill.
Conversational agent model, GroupChat patterns, code execution,
nested chats, cancellation tokens, MCP integration.

All API surfaces validated against microsoft.github.io/autogen docs.

2026-07-09 14:57:27 -04:00

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AutoGen Group Chat

RoundRobinGroupChat

Fixed-order conversation. Each agent speaks in turn.

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.ui import Console

agent1 = AssistantAgent(name="researcher", model_client=model_client)
agent2 = AssistantAgent(name="analyst", model_client=model_client)
agent3 = AssistantAgent(name="writer", model_client=model_client)

team = RoundRobinGroupChat([agent1, agent2, agent3])
result = await team.run(task="Research and write about AI trends")

SelectorGroupChat

LLM-driven speaker selection. Uses a model to decide who speaks next.

from autogen_agentchat.teams import SelectorGroupChat

team = SelectorGroupChat(
    [agent1, agent2, agent3],
    model_client=model_client,  # LLM used for speaker selection
)

MagenticOneGroupChat

Magentic-One orchestrator pattern — a lead agent coordinates specialist agents.

Key Parameters

Parameter	Description
`participants`	List of agents in the group
`model_client`	LLM for speaker selection (SelectorGroupChat)
`max_turns`	Max conversation turns before termination

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